Web System for Monitoring Traps and Managing Images Transmitted via GPRS to Control Diatraea saccharalis in sugarcane cultivation

• Grant number: 24/19261-3
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: April 01, 2025
• End date: March 31, 2026
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computer Systems
• Principal Investigator: Rodrigo Palucci Pantoni
• Grantee: Olavo Lampa Costa
• Host Institution: Instituto Federal de Educação, Ciência e Tecnologia de São Paulo (IFSP). Campus Sertãozinho. Sertãozinho , SP, Brazil

Abstract

This project aims to develop a system for monitoring and controlling the sugarcane borer (Diatraea saccharalis), a pest that affects crops like sugarcane and corn. Using delta traps equipped with IoT devices, the system will transmit images of captured insects via GPRS to a cloud-based database. The project includes creating a web platform for image visualization, leveraging technologies such as JavaScript for the user interface, PostgreSQL for metadata storage, and cloud storage buckets like Amazon S3 for storing the images. Key project stages are: (1) developing the front-end and back-end in JavaScript using the ElysiaJS library to build APIs, (2) integrating HTTPS requests to handle image transmission and retrieval, (3) implementing a PostgreSQL database to store metadata, and (4) configuring cloud storage buckets for secure image storage. Additionally, the project will incorporate a GPRS-based image transmission method and an automatic pest detection algorithm using YOLO to count captured insects. Integration between HTML/JavaScript and Python will be handled via HTTP requests, using frameworks like Flask or Django to process images and deliver responses to the system. The expected outcome is a robust system for managing sugarcane borer infestations, enabling efficient monitoring and timely interventions.